Overview

Dataset statistics

Number of variables7
Number of observations659
Missing cells2142
Missing cells (%)46.4%
Duplicate rows1
Duplicate rows (%)0.2%
Total size in memory37.5 KiB
Average record size in memory58.2 B

Variable types

Numeric2
Text2
DateTime3

Dataset

Description2023년 4월 18일 기준, 경상남도 산청군 태양광발전허가정보입니다. (상호, 설치장소, 설비용량(kW), 허가일자, 사업개시일자 순 제공)
Author경상남도 산청군
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15042031

Alerts

데이터기준일자 has constant value ""Constant
Dataset has 1 (0.2%) duplicate rowsDuplicates
연번 has 306 (46.4%) missing valuesMissing
상호 has 306 (46.4%) missing valuesMissing
설치장소 has 306 (46.4%) missing valuesMissing
설비용량(kW) has 306 (46.4%) missing valuesMissing
허가일자 has 306 (46.4%) missing valuesMissing
사업개시 has 306 (46.4%) missing valuesMissing
데이터기준일자 has 306 (46.4%) missing valuesMissing

Reproduction

Analysis started2023-12-11 00:19:13.371835
Analysis finished2023-12-11 00:19:14.404798
Duration1.03 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

MISSING 

Distinct353
Distinct (%)100.0%
Missing306
Missing (%)46.4%
Infinite0
Infinite (%)0.0%
Mean177
Minimum1
Maximum353
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2023-12-11T09:19:14.464619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile18.6
Q189
median177
Q3265
95-th percentile335.4
Maximum353
Range352
Interquartile range (IQR)176

Descriptive statistics

Standard deviation102.04656
Coefficient of variation (CV)0.57653423
Kurtosis-1.2
Mean177
Median Absolute Deviation (MAD)88
Skewness0
Sum62481
Variance10413.5
MonotonicityStrictly increasing
2023-12-11T09:19:14.572170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
266 1
 
0.2%
242 1
 
0.2%
241 1
 
0.2%
240 1
 
0.2%
239 1
 
0.2%
238 1
 
0.2%
237 1
 
0.2%
236 1
 
0.2%
235 1
 
0.2%
234 1
 
0.2%
Other values (343) 343
52.0%
(Missing) 306
46.4%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
353 1
0.2%
352 1
0.2%
351 1
0.2%
350 1
0.2%
349 1
0.2%
348 1
0.2%
347 1
0.2%
346 1
0.2%
345 1
0.2%
344 1
0.2%

상호
Text

MISSING 

Distinct349
Distinct (%)98.9%
Missing306
Missing (%)46.4%
Memory size5.3 KiB
2023-12-11T09:19:14.779788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length19
Mean length9.4107649
Min length2

Characters and Unicode

Total characters3322
Distinct characters232
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique345 ?
Unique (%)97.7%

Sample

1st row평천태양광발전소
2nd row어울림태양광발전소
3rd row뒷골태양광발전소2호
4th row뒷골태양광발전소 1호
5th row우일1태양광발전소
ValueCountFrequency (%)
태양광발전소 49
 
11.6%
주식회사 9
 
2.1%
지한태양광발전소 2
 
0.5%
행복배가태양광발전소 2
 
0.5%
소남태양광발전소 2
 
0.5%
관정태양광발전소 2
 
0.5%
산청태양광발전소 2
 
0.5%
누리태양광발전소 2
 
0.5%
1호 2
 
0.5%
갈전태양광발전소 2
 
0.5%
Other values (346) 348
82.5%
2023-12-11T09:19:15.092126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
전 336
 
10.1%
소 334
 
10.1%
양 332
 
10.0%
발 330
 
9.9%
태 324
 
9.8%
광 324
 
9.8%
호 93
 
2.8%
70
 
2.1%
2 58
 
1.7%
1 50
 
1.5%
Other values (222) 1071
32.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3068
92.4%
Decimal Number 148
 
4.5%
Space Separator 70
 
2.1%
Open Punctuation 14
 
0.4%
Close Punctuation 14
 
0.4%
Lowercase Letter 5
 
0.2%
Dash Punctuation 2
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 336
 
11.0%
소 334
 
10.9%
양 332
 
10.8%
발 330
 
10.8%
태 324
 
10.6%
광 324
 
10.6%
호 93
 
3.0%
산 48
 
1.6%
청 32
 
1.0%
지 25
 
0.8%
Other values (203) 890
29.0%
Decimal Number
ValueCountFrequency (%)
2 58
39.2%
1 50
33.8%
3 21
 
14.2%
4 6
 
4.1%
5 5
 
3.4%
6 3
 
2.0%
0 3
 
2.0%
8 1
 
0.7%
7 1
 
0.7%
Lowercase Letter
ValueCountFrequency (%)
o 1
20.0%
c 1
20.0%
p 1
20.0%
e 1
20.0%
k 1
20.0%
Space Separator
ValueCountFrequency (%)
70
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Other Punctuation
ValueCountFrequency (%)
: 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3068
92.4%
Common 249
 
7.5%
Latin 5
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 336
 
11.0%
소 334
 
10.9%
양 332
 
10.8%
발 330
 
10.8%
태 324
 
10.6%
광 324
 
10.6%
호 93
 
3.0%
산 48
 
1.6%
청 32
 
1.0%
지 25
 
0.8%
Other values (203) 890
29.0%
Common
ValueCountFrequency (%)
70
28.1%
2 58
23.3%
1 50
20.1%
3 21
 
8.4%
( 14
 
5.6%
) 14
 
5.6%
4 6
 
2.4%
5 5
 
2.0%
6 3
 
1.2%
0 3
 
1.2%
Other values (4) 5
 
2.0%
Latin
ValueCountFrequency (%)
o 1
20.0%
c 1
20.0%
p 1
20.0%
e 1
20.0%
k 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3068
92.4%
ASCII 254
 
7.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
전 336
 
11.0%
소 334
 
10.9%
양 332
 
10.8%
발 330
 
10.8%
태 324
 
10.6%
광 324
 
10.6%
호 93
 
3.0%
산 48
 
1.6%
청 32
 
1.0%
지 25
 
0.8%
Other values (203) 890
29.0%
ASCII
ValueCountFrequency (%)
70
27.6%
2 58
22.8%
1 50
19.7%
3 21
 
8.3%
( 14
 
5.5%
) 14
 
5.5%
4 6
 
2.4%
5 5
 
2.0%
6 3
 
1.2%
0 3
 
1.2%
Other values (9) 10
 
3.9%

설치장소
Text

MISSING 

Distinct289
Distinct (%)81.9%
Missing306
Missing (%)46.4%
Memory size5.3 KiB
2023-12-11T09:19:15.410492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length77
Median length53
Mean length26.991501
Min length19

Characters and Unicode

Total characters9528
Distinct characters154
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique243 ?
Unique (%)68.8%

Sample

1st row경상남도 산청군 신등면 가술리 128-4
2nd row경상남도 산청군 생초면 어서리 123
3rd row경상남도 산청군 신안면 중촌리 482-1
4th row경상남도 산청군 신안면 중촌리 482
5th row경상남도 산청군 산청읍 차탄리 109-10
ValueCountFrequency (%)
경상남도 353
 
16.3%
산청군 352
 
16.3%
단성면 90
 
4.2%
산 68
 
3.1%
금서면 65
 
3.0%
신안면 47
 
2.2%
1호 45
 
2.1%
산청읍 43
 
2.0%
35
 
1.6%
신등면 35
 
1.6%
Other values (475) 1027
47.5%
2023-12-11T09:19:15.826124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1808
19.0%
산 500
 
5.2%
청 404
 
4.2%
1 398
 
4.2%
남 359
 
3.8%
경 358
 
3.8%
상 356
 
3.7%
도 354
 
3.7%
군 353
 
3.7%
면 309
 
3.2%
Other values (144) 4329
45.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5456
57.3%
Decimal Number 1930
 
20.3%
Space Separator 1808
 
19.0%
Dash Punctuation 185
 
1.9%
Other Punctuation 141
 
1.5%
Uppercase Letter 4
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 500
 
9.2%
청 404
 
7.4%
남 359
 
6.6%
경 358
 
6.6%
상 356
 
6.5%
도 354
 
6.5%
군 353
 
6.5%
면 309
 
5.7%
리 299
 
5.5%
지 272
 
5.0%
Other values (125) 1892
34.7%
Decimal Number
ValueCountFrequency (%)
1 398
20.6%
2 248
12.8%
8 191
9.9%
3 187
9.7%
4 174
9.0%
5 168
8.7%
9 151
 
7.8%
6 139
 
7.2%
0 138
 
7.2%
7 136
 
7.0%
Uppercase Letter
ValueCountFrequency (%)
E 2
50.0%
D 1
25.0%
J 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 140
99.3%
. 1
 
0.7%
Space Separator
ValueCountFrequency (%)
1808
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 185
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5456
57.3%
Common 4068
42.7%
Latin 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 500
 
9.2%
청 404
 
7.4%
남 359
 
6.6%
경 358
 
6.6%
상 356
 
6.5%
도 354
 
6.5%
군 353
 
6.5%
면 309
 
5.7%
리 299
 
5.5%
지 272
 
5.0%
Other values (125) 1892
34.7%
Common
ValueCountFrequency (%)
1808
44.4%
1 398
 
9.8%
2 248
 
6.1%
8 191
 
4.7%
3 187
 
4.6%
- 185
 
4.5%
4 174
 
4.3%
5 168
 
4.1%
9 151
 
3.7%
, 140
 
3.4%
Other values (6) 418
 
10.3%
Latin
ValueCountFrequency (%)
E 2
50.0%
D 1
25.0%
J 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5456
57.3%
ASCII 4072
42.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1808
44.4%
1 398
 
9.8%
2 248
 
6.1%
8 191
 
4.7%
3 187
 
4.6%
- 185
 
4.5%
4 174
 
4.3%
5 168
 
4.1%
9 151
 
3.7%
, 140
 
3.4%
Other values (9) 422
 
10.4%
Hangul
ValueCountFrequency (%)
산 500
 
9.2%
청 404
 
7.4%
남 359
 
6.6%
경 358
 
6.6%
상 356
 
6.5%
도 354
 
6.5%
군 353
 
6.5%
면 309
 
5.7%
리 299
 
5.5%
지 272
 
5.0%
Other values (125) 1892
34.7%

설비용량(kW)
Real number (ℝ)

MISSING 

Distinct196
Distinct (%)55.5%
Missing306
Missing (%)46.4%
Infinite0
Infinite (%)0.0%
Mean180.69246
Minimum8.1
Maximum1000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2023-12-11T09:19:15.946742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8.1
5-th percentile13.5
Q148
median98.56
Q399.96
95-th percentile994.95
Maximum1000
Range991.9
Interquartile range (IQR)51.96

Descriptive statistics

Standard deviation268.47402
Coefficient of variation (CV)1.4858064
Kurtosis4.6302799
Mean180.69246
Median Absolute Deviation (MAD)48.8
Skewness2.4373186
Sum63784.44
Variance72078.302
MonotonicityNot monotonic
2023-12-11T09:19:16.058030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
99.0 24
 
3.6%
99.96 20
 
3.0%
97.2 12
 
1.8%
99.9 9
 
1.4%
99.2 6
 
0.9%
10.0 6
 
0.9%
992.0 5
 
0.8%
99.84 5
 
0.8%
97.92 5
 
0.8%
98.8 5
 
0.8%
Other values (186) 256
38.8%
(Missing) 306
46.4%
ValueCountFrequency (%)
8.1 1
 
0.2%
9.0 2
 
0.3%
10.0 6
0.9%
10.08 2
 
0.3%
12.0 1
 
0.2%
12.24 1
 
0.2%
12.96 1
 
0.2%
13.0 2
 
0.3%
13.5 3
0.5%
14.08 1
 
0.2%
ValueCountFrequency (%)
1000.0 3
0.5%
999.96 1
 
0.2%
999.85 1
 
0.2%
999.75 1
 
0.2%
997.92 2
0.3%
997.56 3
0.5%
997.15 1
 
0.2%
996.96 3
0.5%
996.84 1
 
0.2%
996.48 1
 
0.2%

허가일자
Date

MISSING 

Distinct200
Distinct (%)56.7%
Missing306
Missing (%)46.4%
Memory size5.3 KiB
Minimum2007-09-20 00:00:00
Maximum2021-12-08 00:00:00
2023-12-11T09:19:16.187235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:19:16.305008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

사업개시
Date

MISSING 

Distinct239
Distinct (%)67.7%
Missing306
Missing (%)46.4%
Memory size5.3 KiB
Minimum2008-09-16 00:00:00
Maximum2022-02-24 00:00:00
2023-12-11T09:19:16.406056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:19:16.529301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터기준일자
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)0.3%
Missing306
Missing (%)46.4%
Memory size5.3 KiB
Minimum2022-04-15 00:00:00
Maximum2022-04-15 00:00:00
2023-12-11T09:19:16.642813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:19:16.725485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-11T09:19:13.867392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:19:13.687841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:19:13.975171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:19:13.773186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:19:16.781981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번설비용량(kW)
연번1.0000.437
설비용량(kW)0.4371.000
2023-12-11T09:19:16.851638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번설비용량(kW)
연번1.0000.153
설비용량(kW)0.1531.000

Missing values

2023-12-11T09:19:14.107992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:19:14.236238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-12-11T09:19:14.335760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

연번상호설치장소설비용량(kW)허가일자사업개시데이터기준일자
01평천태양광발전소경상남도 산청군 신등면 가술리 128-428.82021-12-082022-02-242022-04-15
12어울림태양광발전소경상남도 산청군 생초면 어서리 12361.22021-10-222021-12-222022-04-15
23뒷골태양광발전소2호경상남도 산청군 신안면 중촌리 482-146.082021-10-202021-12-282022-04-15
34뒷골태양광발전소 1호경상남도 산청군 신안면 중촌리 48299.842021-10-202021-12-282022-04-15
45우일1태양광발전소경상남도 산청군 산청읍 차탄리 109-1099.762021-10-182021-12-202022-04-15
56우일3태양광발전소경상남도 산청군 산청읍 차탄리 109-1089.322021-10-182021-12-202022-04-15
67우일2태양광발전소경상남도 산청군 산청읍 차탄리 109-1099.762021-10-182021-12-202022-04-15
78서재골태양광발전소경상남도 산청군 산청읍 차탄리 527-290.242021-10-082021-12-292022-04-15
89수산2호 태양광발전소경상남도 산청군 단성면 방목리 584-1849.682021-09-172021-11-122022-04-15
910산청차탄태양광발전소경상남도 산청군 산청읍 차탄리 11328.892021-09-032021-11-152022-04-15
연번상호설치장소설비용량(kW)허가일자사업개시데이터기준일자
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657<NA><NA><NA><NA><NA><NA><NA>
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연번상호설치장소설비용량(kW)허가일자사업개시데이터기준일자# duplicates
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